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Results: 24
Number of items: 24
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Hupkes, D., & Zuidema, W. (2017). Diagnostic classification and symbolic guidance to understand and improve recurrent neural networks. Paper presented at Interpreting, Explaining and Visualizing Deep Learning workshop, Long Beach, California, United States. http://www.interpretable-ml.org/nips2017workshop/papers/12.pdf -
Hupkes, D., Veldhoen, S., & Zuidema, W. (2017). Visualisation and 'diagnostic classifiers' reveal how recurrent and recursive neural networks process hierarchical structure. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.1711.10203
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Hupkes, D., & Bod, R. (2016). POS-tagging of Historical Dutch. In N. Calzolari, K. Choukri, T. Declerck, S. Goggi, M. Grobelnik, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, & S. Piperidis (Eds.), LREC 2016 : Tenth International Conference on Language Resources and Evaluation: May 23-28, 2016, Grand Hotel Bernardin Conference Center, Portorož, Slovenia (pp. 77-82). European Language Resources Association (ELRA). http://www.lrec-conf.org/proceedings/lrec2016/summaries/196.html
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Veldhoen, S., Hupkes, D., & Zuidema, W. (2016). Diagnostic Classifiers: Revealing how Neural Networks Process Hierarchical Structure. In T. R. Besold, A. Bordes, A. d'Avila Garcez, & G. Wayne (Eds.), Proceedings of the Workshop on Cognitive Computation: Integrating neural and symbolic approaches 2016: co-located with the 30th Annual Conference on Neural Information Processing Systems (NIPS 2016) : Barcelona, Spain, December 9, 2016 Article 6 (CEUR Workshop Proceedings; Vol. 1773). CEUR-WS. http://ceur-ws.org/Vol-1773/CoCoNIPS_2016_paper6.pdf
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